Hierarchical mixtures of experts and the EM algorithm
Neural Computation
Convex potentials and their conjugates in analog mean-field optimization
Neural Computation
Inducing Features of Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Exponentiated gradient versus gradient descent for linear predictors
Information and Computation
A view of the EM algorithm that justifies incremental, sparse, and other variants
Learning in graphical models
Convergence properties of the softassign quadratic assignment algorithm
Neural Computation
An Introduction to Variational Methods for Graphical Models
Machine Learning
Pairwise Data Clustering by Deterministic Annealing
IEEE Transactions on Pattern Analysis and Machine Intelligence
A novel optimizing network architecture with applications
Neural Computation
A Double-Loop Algorithm to Minimize the Bethe Free Energy
EMMCVPR '01 Proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Stochastic reasoning, free energy, and information geometry
Neural Computation
Combined SVM-Based Feature Selection and Classification
Machine Learning
A regularization framework for multiple-instance learning
ICML '06 Proceedings of the 23rd international conference on Machine learning
Trading convexity for scalability
ICML '06 Proceedings of the 23rd international conference on Machine learning
Simpler knowledge-based support vector machines
ICML '06 Proceedings of the 23rd international conference on Machine learning
Efficient MAP approximation for dense energy functions
ICML '06 Proceedings of the 23rd international conference on Machine learning
Expectation Consistent Approximate Inference
The Journal of Machine Learning Research
Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming
The Journal of Machine Learning Research
Multiple instance learning for sparse positive bags
Proceedings of the 24th international conference on Machine learning
Sparse eigen methods by D.C. programming
Proceedings of the 24th international conference on Machine learning
Optimization Techniques for Semi-Supervised Support Vector Machines
The Journal of Machine Learning Research
Discriminatively regularized least-squares classification
Pattern Recognition
Semi-supervised Discriminant Analysis Via CCCP
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
Robust support vector regression in the primal
Neural Networks
A majorization-minimization algorithm for (multiple) hyperparameter learning
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Convex variational Bayesian inference for large scale generalized linear models
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Learning structural SVMs with latent variables
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Instance-level semisupervised multiple instance learning
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Maximum margin clustering made practical
IEEE Transactions on Neural Networks
Robust truncated support vector regression
Expert Systems with Applications: An International Journal
Analysis of Multi-stage Convex Relaxation for Sparse Regularization
The Journal of Machine Learning Research
Linear time maximum margin clustering
IEEE Transactions on Neural Networks
A soft multiphase segmentation model via Gaussian mixture
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Pattern Recognition Letters
Fast and Scalable Local Kernel Machines
The Journal of Machine Learning Research
Multi-level structured models for document-level sentiment classification
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
A generic framework for event detection in various video domains
Proceedings of the international conference on Multimedia
An improved smoothed l0approximation algorithm for sparse representation
IEEE Transactions on Signal Processing
Learning ECOC and dichotomizers jointly from data
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I
The LCCP for optimizing kernel parameters for SVM
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
A new framework of multiphase segmentation and its application to partial volume segmentation
Applied Computational Intelligence and Soft Computing
Can irrelevant data help semi-supervised learning, why and how?
Proceedings of the 20th ACM international conference on Information and knowledge management
Multi-instance multi-label learning
Artificial Intelligence
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
SIAM Journal on Imaging Sciences
Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services
Skew jensen-bregman voronoi diagrams
Transactions on Computational Science XIV
Structured Learning and Prediction in Computer Vision
Foundations and Trends® in Computer Graphics and Vision
Multiple kernel learning with gaussianity measures
Neural Computation
Modeling disease progression via fused sparse group lasso
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Feature selection via dependence maximization
The Journal of Machine Learning Research
Review: Supervised classification and mathematical optimization
Computers and Operations Research
Research history generation from metainformation of research papers using maximum margin clustering
International Journal of Business Intelligence and Data Mining
Fine granular aspect analysis using latent structural models
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers - Volume 2
Learning to map into a universal POS tagset
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Hausdorff distance constraint for multi-surface segmentation
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part I
Information Sciences: an International Journal
Coupling-and-Decoupling: a hierarchical model for occlusion-free car detection
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Indexed block coordinate descent for large-scale linear classification with limited memory
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning latent spatio-temporal compositional model for human action recognition
Proceedings of the 21st ACM international conference on Multimedia
Regularized bundle methods for convex and non-convex risks
The Journal of Machine Learning Research
Sparse high-dimensional fractional-norm support vector machine via DC programming
Computational Statistics & Data Analysis
Binary classification via spherical separator by DC programming and DCA
Journal of Global Optimization
Exploring weakly supervised latent sentiment explanations for aspect-level review analysis
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Learning from M/EEG data with variable brain activation delays
IPMI'13 Proceedings of the 23rd international conference on Information Processing in Medical Imaging
Robust feature selection for SVMs under uncertain data
ICDM'13 Proceedings of the 13th international conference on Advances in Data Mining: applications and theoretical aspects
DCA based algorithms for feature selection in semi-supervised support vector machines
MLDM'13 Proceedings of the 9th international conference on Machine Learning and Data Mining in Pattern Recognition
Recognizing human-human interaction activities using visual and textual information
Pattern Recognition Letters
Maximum volume clustering: a new discriminative clustering approach
The Journal of Machine Learning Research
Multi-stage multi-task feature learning
The Journal of Machine Learning Research
Spontaneous clustering via minimum gamma-divergence
Neural Computation
Object and Action Classification with Latent Window Parameters
International Journal of Computer Vision
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The concave-convex procedure (CCCP) is a way to construct discrete-time iterative dynamical systems that are guaranteed to decrease global optimization and energy functions monotonically. This procedure can be applied to almost any optimization problem, and many existing algorithms can be interpreted in terms of it. In particular, we prove that all expectation-maximization algorithms and classes of Legendre minimization and variational bounding algorithms can be reexpressed in terms of CCCP. We show that many existing neural network and mean-field theory algorithms are also examples of CCCP. The generalized iterative scaling algorithm and Sinkhorn's algorithm can also be expressed as CCCP by changing variables. CCCP can be used both as a new way to understand, and prove the convergence of, existing optimization algorithms and as a procedure for generating new algorithms.